Ponomarenko et al. BMC Medical Genetics 2020, 21(Suppl 1):165
https://doi.org/10.1186/s12881-020-01106-x

RESEARCH

Open Access

Unannotated single nucleotide
polymorphisms in the TATA box oferythropoiesis genes show in vitro positive
involvements in cognitive and mental
disorders
Mikhail Ponomarenko1,2* , Ekaterina Sharypova1, Irina Drachkova1, Irina Chadaeva1, Olga Arkova3,
Olga Podkolodnaya1, Petr Ponomarenko1, Nikolay Kolchanov1 and Ludmila Savinkova1
From 11th International Young Scientists School “Systems Biology and Bioinformatics” – SBB-2019
Novosibirsk, Russia. 24-28 June 2019

Abstract
Background: Hemoglobin is a tetramer consisting of two α-chains and two β-chains of globin. Hereditary aberrations inthe synthesis of one of the globin chains are at the root of thalassemia, one of the most prevalent monogenic diseases
worldwide. In humans, in addition to α- and β-globins, embryonic zeta-globin and fetal γ-globin are expressed. Immediately
after birth, the expression of fetal Aγ- and Gγ-globin ceases, and then adult β-globin is mostly expressed. It has been shownthat in addition to erythroid cells, hemoglobin is widely expressed in nonerythroid cells including neurons of the cortex,
hippocampus, and cerebellum in rodents; embryonic and adult brain neurons in mice; and mesencephalic dopaminergic
brain cells in humans, mice, and rats. Lately, there is growing evidence that different forms of anemia (changes in thenumber and quality of blood cells) may be involved in (or may accompany) the pathogenesis of various cognitive andmental disorders, such as Alzheimer’s and Parkinson’s diseases, depression of various severity levels, bipolar disorders, andschizophrenia. Higher hemoglobin concentrations in the blood may lead to hyperviscosity, hypovolemia, and lung diseases,
which may cause brain hypoxia and anomalies of brain function, which may also result in cognitive deficits.
Methods: In this study, a search for unannotated single-nucleotide polymorphisms (SNPs) of erythroid genes was initiallyperformed using our previously created and published SNP-TATA_Z-tester, which is a Web service for computational analysis
of a given SNP for in silico estimation of its influence on the affinity of TATA-binding protein (TBP) for TATA and TATA-likesequences. The obtained predictions were finally verified in vitro by an electrophoretic mobility shift assay (EMSA).
(Continued on next page)* Correspondence: pon@bionet.nsc.ru
1
Institute of Cytology and Genetics, Siberian Branch of Russian Academy of
Sciences, 10 Lavrentyev Ave, Novosibirsk 630090, Russia
2
Novosibirsk State University, 1 Pirogova Street, Novosibirsk 630090, Russia
Full list of author information is available at the end of the article© The Author(s). 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License,
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Ponomarenko et al. BMC Medical Genetics 2020, 21(Suppl 1):165

Page 2 of 14(Continued from previous page)

Results: On the basis of these experimental in vitro results and literature data, we studied TATA box SNPs influencing bothhuman erythropoiesis and cognitive abilities. For instance, TBP–TATA affinity in the HbZ promoter decreases 6.6-fold as aresult of a substitution in the TATA box (rs113180943), thereby possibly disrupting stage-dependent events of “switching” ofhemoglobin genes and thus causing erythroblastosis. Therefore, rs113180943 may be a candidate marker of severe
hemoglobinopathies with comorbid cognitive and mental disorders associated with cerebral blood flow disturbances.
Conclusions: The literature data and experimental and computations results suggest that the uncovered candidate
SNP markers of erythropoiesis anomalies may also be studied in cohorts of patients with cognitive and/or mental
disorders with comorbid erythropoiesis diseases in comparison to conventionally healthy volunteers. Research into theregulatory mechanisms by which the identified SNP markers contribute to the development of hemoglobinopathies
and of the associated cognitive deficits will allow physicians not only to take timely and adequate measures against
hemoglobinopathies but also to implement strategies preventing cognitive and mental disorders.
Keywords: Erythropoiesis, Cognitive disorder, In silico prediction, TBP/TATA affinity, kinetics of TBP-TATA bindingin vitro, TATA-binding protein, SNP marker

Background
According to World Health Organization estimates, ~ 7% of
the world population have hereditary aberrations in the synthesis of hemoglobin, meaning that these are the most prevalent monogenic disorders [1]. Alpha- and β-thalassemia andsickle cell anemia are the most prevalent autosomal recessive
diseases caused by mutations in the genes of α- and β-globin.
β-Thalassemia was first documented in the Mediterranean,
Middle-Eastern, and Asian regions, whereas sickle cellanemia was first documented in Central Africa. As a resultof increasing population migration, these diseases are currently global and therefore represent a growing problem for
health care in many countries. The spread of these diseases
is also promoted by natural selection favoring carriers ofhemoglobin synthesis aberrations who are relatively resistantto the malaria caused by Plasmodium falciparum [2].
It is known that human hemoglobin, the protein thatcarries oxygen from the lungs to various tissues, is a tetramer consisting of two α-subunits and two β-subunits ofglobin. Aberration one of the globin chains are the reasonof thalassemia that is one of the most prevalent monogenic diseases all over worldwide [3]. Patients with severethalassemia have serious problems related to life-longblood transfusion dependence; besides, they develop severe anemia, chronic hemolysis, and iron overload of various organs as a result of inefficient erythropoiesis, which
launches compensatory mechanisms leading to, among
other problems, elevated iron absorption in the heart andgastrointestinal tract [4], hepatosplenomegaly, and suchcomplications as cardiopathy and endocrine disturbances[4]. Patients with mild thalassemia may not experience thedisease manifestations and may not have anemia. αThalassemia, caused by deletion of one or both α-globin
genes located on chromosome 16, is characterized by analmost asymptomatic clinical phenotype. The deletion of
three or four genes of α-globin (Bart disease is caused by
the deletion of all four genes) is characterized by a severeor lethal form of hemolytic anemia, respectively [5], where
α-globin is not synthesized at all, and this condition causes
fetal death (prenatal or at birth) [6]. α-Thalassemia is associated with a fairly rare syndrome of intellectual disability,
ATR-X (α-thalassemia X-linked mental retardation),
which features moderate or severe intellectual disability,
delayed development, and other problems [7].
In addition to α- and β-globins, there are embryoniczeta-globin and fetal γ-globin in humans. Immediately
after birth, the expression of fetal Aγ- and Gγ-globin
stops, and then adult β-globin is expressed mostly [8].
It has been reported that in addition to erythroid cells,
hemoglobin is widely expressed in nonerythroid cells including neurons of the cortex, hippocampus, and cerebellum in rodents [9]; embryonic and adult brain neurons inmice [10]; and mesencephalic dopaminergic brain cells inhumans, mice, and rats [11]. Lately, there is growing evidence that different forms of anemia may be involved inor accompany the pathogenesis of various cognitive andmental disorders, such as Alzheimer’s and Parkinson’s diseases, depression of various severity levels, and bipolar disorders [12–14]. Severe depressive disorders are the third
leading cause of disability worldwide [15]. Bipolar disorder
is a severe psychiatric illness that starts as mild depression
and brief hypomania and progresses to the acute phasewith manic episodes [16].
It is known that the brain responds to a lowered
hemoglobin level during anemia with vasodilation increasing
cerebral blood flow. Nonetheless, when hemoglobin concentration drops substantially, the aforementioned compensatory mechanism is not triggered, and cerebral blood flow
becomes insufficient, leading to brain function deficits and ischemia [17]. Both clinical [18, 19] and subclinical ischemia[20] are risk factors of mild cognitive impairment and dementia. The associations with anemias, in particular withmicrocytic anemia, which is most often iron deficient, may
be related to oxidative stress in the brain, as a consequencePonomarenko et al. BMC Medical Genetics 2020, 21(Suppl 1):165

of poor or ineffective iron assimilation [21]. Elevatedhemoglobin levels can cause blood hyperviscosity, hypovolemia, and lung diseases, which may result in brain hypoxia
and anomalies of brain function, which may also cause cognitive deficits [22]. The incidence and prevalence of anemia
and hyperhemoglobinemia increase with age [23]. This stateof affairs has prompted more targeted research into
hematopoiesis disturbances to elucidate their mechanisms in
relation to possible cognitive deficits.
Previously, by annotating experimental results fromvarious authors, we have compiled a list of singlenucleotide polymorphism (SNP)-containing TATA boxesof human genes [24] associated with diverse hereditarymonogenic diseases. The link between SNPs and diseases
has been proven by those authors both molecularly andclinically. By means of the stepwise interaction of TATAbinding protein (TBP) with a TATA box [25], the sequences of TATA boxes with the surrounding nucleotides
have been analyzed, and in silico predictions have been
made regarding the influence of each SNP on TBP–TATA
affinity. Subsequently, experimental in vitro verification ofthese in silico predictions has been conducted [26, 27] revealing a coefficient of correlation (r; between the prediction and experiment) of 0.822 at p < 10− 7.
After the completion of the “1000 Genomes” project [28],more than 10 thousand individual human genomes havebeen successfully sequenced [29], and 8.6 × 109 possible
SNPs have been deposited in the dbWGFP database [30].
Undoubtedly, these numerous SNPs require preliminary filtration in silico before costly and labor-intensive studies
in vitro, ex vivo, and in vivo. With a high degree of certainty,
it can be assumed that the number of identified SNPs in
TATA boxes has increased substantially since 2009. Theseobservations motivated us to update the list of previously
documented TATA box SNPs in the promoters of humanhemoglobin genes. Using publicly available online databases,in this work we selected unannotated SNPs of the promotersof genes associated with erythropoiesis, which were analyzed
by means of our public Web service SNP_TATA_Z-tester[31], developed within the framework of the three-step biophysical model for TBP binding to TATA-like boxes [25],namely: (i) TBP slides along DNA ↔ (ii) TBP stops at a
TBP-binding site [TATA-box] ↔ (iii) the TBP–promoter
complex is fixed by a 90O bend of DNA, − as in vitro independently observed experimentally in solution [32]. The
Web service has been used by us previously to predict candidate SNP markers in TATA boxes in the context of realworld promoters of genes related to reproductive potential[33], aggressiveness [34], Alzheimer’s disease [35], obesity[36], chronopathologies [37], and autoimmune diseases [37].
In the present study, after in silico analysis of 161 unannotated SNPs, 45 candidate SNP markers were predicted for 15
out of the 25 genes participating in erythropoiesis and showing changes in TBP–TATA box affinity in the promoter.

Page 3 of 14

Some of them were chosen for experimental validationin vitro. A possible link between cognitive deficits and the influence of SNPs from TATA boxes and TATA-like sequences on the promoters of hematopoiesis genes is also
discussed.

Methods
DNA sequences

We performed a search and retrieval of data from thedatabases of unannotated SNPs in the TATA boxes oferythroid genes. We employed Web service SNP_TATA_Z-tester [31], developed within the framework of
the stepwise model for TBP binding to TATA-like boxes[25]. Using this software, we analyzed unannotated substitutions in the TATA boxes of human hemoglobin
genes (HBZ, HBB, HBD, and HBG1) and the genes encoding the enzymes participating in heme biosynthesis(ALAS1, CA1, EPOR, and GYPC) and other proteins (involved in erythropoiesis): a total of 161 SNPs from 25
human genes. These data are publicly available thanks to
Web service UCSC Genome Browser [38]. Computational analysis of 8.58 × 109 possible SNPs throughout
the whole human genome, predictions, experimental
data, and the relevant clinical findings accumulated indatabase dbWGFP may accelerate and orient the clinicalsearch for biomedical markers [30].
Genes directly participating in the processes of proliferation, differentiation, and maturation of erythrocytes inhumans were retrieved from database ESGR-TRRD(erythroid-cell–specific regulated genes in TRRD format),created by Podkolodnaya O.A. and Stepanenko I.L.
(http://wwwmgs.bionet.nsc.ru/mgs/papers/podkolodnaya/
esg-trrd) for humans, chickens, rabbits, mice, rats, andzebrafish. The numbers of promoters, their sequences in
the region [− 100; − 1] relative to the transcription startsite in the 22 erythroid genes under study as well as thepresence or absence of TATA boxes in these genes were
determined in the Eukaryotic Promotor Database (EPD).
Physical coordinates of each promoter were found in database UCSC (build 38 or GRCh38/hg38) via the BLAST
software (rapidly aligning sequences to the genome). The
SNPs present in promoters were retrieved from the UCSC
database (build 38 or GRCh38/hg38) via a resource called
Browser (to download data from the Genome Browser
database). Sequence data for the substitutions and their
populational characteristics were obtained from database
dbSNP [39] (Database of Single Nucleotide Polymorphisms) at the National Center for Biotechnology Information (NCBI; Bethesda, MD, USA).
DNA sequence analysis in silico

We analyzed DNA sequences between nucleotide positions − 100 and − 1 upstream of the protein-coding regions in the human genes retrieved from the humanPonomarenko et al. BMC Medical Genetics 2020, 21(Suppl 1):165

reference genome using our Web service SNP_TATA_
Z-tester.
Synthetic double-helical deoxyoligonucleotides (ODNs)

The ODNs corresponding to ancestral and minor allelesof the selected SNPs were synthesized and purified(Biosset, Novosibirsk, Russia).
Labeling of the ODNs with 32P

The ODNs were 26 bp long; they were synthesized and additionally purified by polyacrylamide gel (PAAG) electrophoresis at Biosset (Novosibirsk). To prepare a labeled doublestranded ODN, both strands were labeled with 32P-ATP(Biosan, Novosibirsk) by means of Т4 polynucleotide kinase(SibEnzyme, Novosibirsk), annealed at 95 °C (in the equimolar ratio), and were slowly cooled (no less than 3 h) to room
temperature. The annealed duplexes were purified and analyzed by electrophoresis in a 15% PAAG under nondenaturing conditions with subsequent autoradiography on a
Molecular Imager PharosFX Plus phosphorimager (Bio-Rad)[40]. Unlabeled duplexes were prepared in the same way andwere used after the additional purification by electrophoresis.
Preparation and purification of recombinant full-length
human TBPIn this study, recombinant human TBP (hTBP) was
employed that was expressed in Escherichia coli
BL21(DE3) cells from plasmid pAR3038-hTBP (kindly
provided by Prof. B. Puhg, Center for Gene Regulation,
Department of Biochemistry and Molecular Biology, The
Pennsylvania State University, University Park, PA,
USA). Transformation of E. coli BL21(DE3) was performed as described elsewhere [41]. Expression andpurification of TBP were carried out as described previously [42], except for isopropyl β-D-1-thiogalactopyranoside (IPTG) concentration (1.0 instead of 0.1 mM) and
induction duration (3.0 instead of 1.5 h).
Determination of the association and dissociation rate
constants of TBP–ODN complexes

Experiments on TBP–ODN binding were conducted at
25 °C in a buffer consisting of 20 mM HEPES-KOH (pH7.6), 5 mM MgCl2, 70 mM KCl, 1 mM dithiothreitol,
100 μg/ml BSA, 0.01% of NP-40, and 5% of glycerol witha fixed concentration of active TBP (usually 0.5 nM).
To determine the kinetic constants of the associationand dissociation of complexes, at least three independent
experiments were conducted. Each experiment on kinetics usually included 32 binding reactions (eight time
points, each with four concentrations of an ODN). Allfour binding reactions (one time point) were started
simultaneously by the addition of TBP into the reaction
mixture containing an ODN, with immediate transfer toa thermostat at 25 °C. Upon completion of the binding

Page 4 of 14

reaction, all the reaction mixtures were applied to a
PAAG concurrently at electric-field intensity of 10 V/
cm. TBP–ODN complexes were separated from the unbound ODN by an electrophoretic mobility shift assay.
The electrophoresis was performed in a native 5% PAAG
based on Tris-glycine buffer (pH 8.3) for 40 min at 10°С
and electric-field intensity 25 V/cm. The gels were dried
and used for exposure of a screen, Imaging Screen-K(Kodak), on the Molecular Imager PharosFX Plus phosphorimager (Bio-Rad). The screen was scanned on thephosphorimager, and the autoradiograph was analyzed
quantitatively in the Quantity One software, version
4.5.0 (Bio-Rad). Velocity constants and equilibrium constants of dissociation of TBP–ODN complexes were calculated in GraphPad Prism 5 (GraphPad Software, San
Diego, CA, USA).
Statistical analysis

A comparison of our predictions with the experimental
values of changes in TBP–TATA affinity after the substitutions in TATA boxes was conducted by means of two options, “Multiple Regression” and “Nonparametrics,” in thestandard software STATISTICA (Statsoft™, Tulsa, USA).
Changes in KD (δ) with an SNP in the TATA box were calculated as -ln [KD,TATAMut] – (−ln [KD,TATA]).

Results and DISCUSSIONSIn silico analysis of human erythropoiesis genes

Tables 1 and 2 show unannotated SNPs of TATA boxes
from the promoters of erythropoiesis genes; these SNPs
were retrieved from publicly available databases. Predictions were made via Web service SNP_TATA_Z-tester,which is a modified version of the SNP_TATA_Z-tester
Web service [31], as illustrated in the example presented
in Fig. 1.
The cluster of human β-globin genes consists of fivegenes (5′-ε-γG-γA-δ-β-3′) and a locus control region[44]. Clinical manifestations of β-thalassemia (MIM
613985) mostly depend on the mutations in the regulatory
and structural regions of the β-globin gene [45]. In the severe form of the disease, these manifestations consist of
stunted growth, paleness, jaundice, hepatosplenomegaly,
skeletal changes, and other problems as well as complications related to iron overload, including a wide range of
endocrine disturbances (stunted growth, disorder of sexual maturity, diabetes mellitus and hypothyroidism, pituitary failure, and more rarely, adrenal insufficiency), dilated
cardiomyopathy, and liver fibrosis and cirrhosis [46]. In
patients with intermediate thalassemia, osteoporosis ispresent, as is the involvement of the spleen, liver, andlymph nodes as well as bone deformity, gallbladder stones,
and higher susceptibility to thromboses. Mild thalassemia
may be asymptomatic. It has been demonstrated that in
the human genes encoding β- and δ-hemoglobins (HBB

Ponomarenko et al. BMC Medical Genetics 2020, 21(Suppl 1):165

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Table 1 Predictions of the influence of SNPs in the promoters of the hemoglobin subunit genes on TBP–TATA affinity, as performedby SNP-TATA-Z-tester [31]GeneAlleles, WT or mut

DNA sequence, TATA-like box; 5′-3′

Prognosis, −ln KD

HBB

WT
rs63750400:G
rs281864525:T
rs34598529:G
rs33980857:A
rs33980857:C
rs33980857:G
rs33981098:C
rs33981098:A
rs34500389:T
rs34500389:A
rs33931746:C

cagggctgggcataaaactcagggcagag
cagggctgggcataaaaGtcagggcagag
cagggctgggcataaaTctcagggcagag
cagggctgggcatGaaactcagggcagag
cagggctgggcaAaaaactcagggcagag
cagggctgggcaCaaaactcagggcagag
cagggctgggcaGaaaactcagggcagag
cagggctgggcCtaaaactcagggcagag
cagggctgggcGtaaaattcagggcagag
cagggctgggTataaaactcagggcagag
cagggctgggActaaaactcagggcagag
cagggctgggcataCaactcagggcagag

19.20
19.12
19.16917.84917.70118.17217.67318.55318.062
20.17518.63518.341

HBB_2

WT
rs35518301:G

ggaccagcacaaaaggcagggcagag
ggaccagcacGaaaggcagggcagag

19.29
18.65

HBZ

WT
rs113180943:T
rs1035033590:C

cagctccctgtaataaggggaccctg
cagctccctgtaTtaaggggaccctg
cagctccctgtaataaggCgaccctg

20,76
19,28
20,773

HBZ_3

WT
rs559282746:G

ggagggtggggcccctatctctcct
ggagggtggggcGcctatctctcct

17.61117.605

HBA1

WT
rs571582665:T

gcgccccaagcataaacctggcgcgc
gcgccccaagcataaacTtggcgcgc

18.36
18.62

HBG1

WT
rs573241527:G

agggtgcttccttttattcttcatcc
agggtgcttccttttCttcttcatcc

19.06
17.54

HBM

WT
rs905730148:A
rs937192507:C

ggtgcccggaggctctataaggaggc
ggtgcccggagAccctataaggaggc
ggtgcccggaggcccCataaggaggc

19.13
19.23
19.95

HBE1

WT
rs768296486:A
rs1036491581:G
rs150246840:C

aggcaaaaagagagcttgtgtagagc
aggcaaaaagagagAttgtgtagagc
aggcaaaaagagagaGtgtgtagagc
aggcaaaaagagaggttgtgtagCgc

18.31
18.16
18.01
18.16

Notes: Ancestral (WT) and minor (mut) alleles; KD, dissociation constant of the TBP–DNA complex [13]; Genes: HBB, β-globin; HBB_2, β-globin promoter 2; HBZ
zeta-globin; HBZ_3 zeta-globin promoter 3; HBA1, α1-globin; HBG1 Aγ globin; HBM Hemoglobin subunit μ; and HBE1 ε-globinand HBD, respectively), six of many regulatory SNP
markers (rs33981098, rs33980857, rs34598529, rs3393
1746, rs397509430, and rs35518301) weaken the affinity
between TBP and the promoter of these genes and cause
both thalassemia and resistance to malaria [47]. By contrast, one SNP marker (rs34500389) that enhances this affinity was found only once during the screening of
newborns in Spain without any symptoms of thalassemia,
i.e., this SNP allele was assumed to be harmless [48].
The zeta-globin gene (HBZ) codes for an αpolypeptide that is synthesized in the yolk sac of anearly embryo, whereas α-globin is produced throughout the lifespan of the fetus and adult person. HBZ isa member of the cluster of human α-globin genes,
which includes five functional genes and two pseudogenes [49]. This cluster features deletions of long segments (the most prevalent ones are the so-called
Mediterranean deletion, Southeastern deletion, andThai deletion), including α-globin genes, thereby
causing α-thalassemia [50, 51]. The Zeta2 gene isexpressed at the embryonic stage and is also subject
to deletion [51].

In hemoglobinopathies, mutations in DNA simultaneously influence the expression of several genes, e.g., γglobin genes (HBG1 and HBG2), responsible for the synthesis of γ-chains, which are present in fetal hemoglobin(HbF) [52]. Regulatory sequences of the 5′ region of
HBG1 and HBG2 promoters contain at least eight SNP
markers, which are located outside the core promoter
region studied by us [− 100; − 1]. The main function ofpromoter elements of HBG1 and HBG2 is the binding totranscription complexes, which inhibit the expression of
fetal hemoglobin at an appropriate stage [53, 54]. Unannotated rs573241527, which was detected by us, replaces
Т by G in the TATA box of the HBG1 promoter(Table 1) and is predicted to lower the affinity of theinteraction with TBP.
The 5′-aminolevulinate synthase 1 gene (ALAS1) encodes a mitochondrial matrix enzyme, which catalyzes
the first, rate-limiting stage of heme biosynthesis [55].
The most well-known role of ALAS1 is catalysis of thecondensation of glycine and succinyl-coenzyme A forformation of 5′-aminolevulinate; the latter is a universal
precursor of tetrapyrrole compounds participating inPonomarenko et al. BMC Medical Genetics 2020, 21(Suppl 1):165

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Table 2 Predictions regarding the influence of SNPs in the promoters of erythroid genes (except the hemoglobin subunit genes) on
TBP–TATA affinity, as performed by SNP-TATA-Z-tester [31]GeneAlleles: WT or mut

DNA sequence, TATA-like box; 5′-3′

Prognosis, −ln KD

ALAS1

WT
rs564394089:A
rs1046254329:A
rs905035347:T

ctcccgctgtatattaaggcgccggc
ctacAgctgtatattaaggcgccggc
ctaccgctAtatattaaggcgccggc
ctaccgctatatattaaggTgccggc

20.11
20.23
20.40
20.11

CA1

WT
rs540950375:T
rs991064314:T

ggaatgggcagcttatgtacaggggg
ggaatgggcaTcttatgtacaggggg
ggaatgggTagcttatgtacaggggg

19.81
19.70
19.82

CA1_2

WT
rs557418569:G
rs538698304:C

cttgggcatttttatagaaacttact
cttgggcGtttttatagaaacttact
cttgggcattttCatagaaacttact

20.22
20.16
19.61

HOXB2

WT
rs762972656:T

aggactccagcgaaattacagggaat
aggactccaTcgaaattacagggaat

17.98
17.92

EPOR

WT
rs1006576690:T
rs971717705:C
rs567946217:A
rs567946217:C

cgtagcagacaaaaatagatgacgtg
cgtagcagacaaaTatagatgacgtg
cgtagcagacaaaaaCagatgacgtg
cgtagcagacaaaaataAatgacgtg
cgtagcagacaaaaataCatgacgtg

18.24
19.39
18.11
19.33
18.51

GYPB

WT
rs3967038:C
rs3967038:A

gcctactagctgttatcttccaggcc
gcctacCagctgttatcttccaggcc
gcctacAagctgttatcttccaggcc

18.26
18.30
18.23

GYPC

WT
rs970970552:A
rs911469201:A
rs989175270:G

cattggggagttttccctgcactcct
cattAgggagttttccctgcactcct
cattggggagttttccctAcactcct
cattggggagttttccctgGactcct

16.97
17.83
17.13
17.27

EDRF1

WT
rs946240545:G
rs774081749:G
rs895690311:G

tcgcgagatttaatggcgagtcacag
tcgcgagGtttaatggcgagtcacag
tcgcgagattGaatggcgagtcacag
tcgcgagatttaatggcgGgtcacag

18.45
18.34
17.76
18.18

Notes: See “Notes” under Table 1. Genes: ALAS1 Aminolevulinate synthase 1; CA1 Carbonic anhydrase 1; CA1_2 Carbonic anhydrase promoter 2; HOXB2 Homeobox
B2; EPOR Erythropoietin receptor; GYPB Glycophorin B; GYPC Glycophorin C; and EDRF1 Erythroid differentiation regulatory factor 1

various reactions, including heme biosynthesis, singleelectron transfer, and catalysis of redox reactions [56,57]. It is reported that there is substantial tissue-specificexpression and heme-mediated (as a feedback loop)
regulation of enzymes in the heme biosynthesis pathway[8]. In particular, it is known that ALAS exists in theform of tissue-specific isozymes, that is, erythroid andnonspecific ALAS, which are encoded by two different
genes. Unannotated rs1046254329 (G > A)—detected by
us in the TATA box of the promoter—is predicted toslightly enhance TBP–TATA affinity, as readers can see
in Table 2.
Carbonic anhydrases (CA) are zinc metalloenzymes thatcatalyze reversible hydration of carbon dioxide to the bicarbonate ion and proton [58, 59]. At present, there are
15 known CA isozymes belonging to the α class. CA isozymes have different distribution profiles among tissues
and organs and different subcellular localizations, catalytic
activities, and physiological functions [60]. The carbonic
anhydrase family (CA1, − 2, and − 3) performs a multitudeof functions in various species. It is known that CA1 takes
part in homeostasis, mitochondrial respiration, and erythroid differentiation and may be involved in such

pathological processes as anemia, chronic acidosis, anddiabetic macular edema [60]. Unannotated rs538698304
detected by us in three separate projects on population research is regarded as rare: its minor allele frequencies are
0.00006, 0.0001, and 0.0002. This substitution in the middle of the TATA box of the CA1 promoter worsens the
TATA box sequence, and according to our prediction,
lowers TBP–TATA affinity. Therefore, this SNP may be a
candidate marker of anemia.
In addition to erythropoiesis regulation in hematopoietic
tissues, erythropoietin (EPO) functions in other tissues, including the nervous system. To perform its function, EPO
uses a homodimeric receptor (EPOR), which is also widely
expressed in the nervous system [61]. The main role of
EPOR is to stimulate the rapid spread of erythrocyte progenitors and to promote their survival [62]. Mutations of
EPOR cause primary hereditary erythrocytosis [63] andhave been detected in 15% of the cases [64]. It is wellproven that the EPO/EPOR system has a wide spectrumof nonhematopoietic effects [64]. Functional receptors
encoded by EPOR have been discovered in nonerythroid
blood cell lineages, such as lymphocytes, myeloid cells,
and megakaryocytes. Besides, EPOR is widely expressed inPonomarenko et al. BMC Medical Genetics 2020, 21(Suppl 1):165

Page 7 of 14

Fig. 1 Candidate SNP marker rs34500389 predicted by this work to be associated with mental and cognitive disorders. Legend: a Unannotated
SNPs (analyzed in this study) in the 100 bp region [where all known TBP-binding sites (boxed) are located; double-headed arrow, ↔] of thehuman HBB gene promoter were examined using the UCSC Genome Browser [38]. Dotted-and-dashed arrow: SNP rs34500389 under study within
the reference human genome sequence and its description within database dbSNP [39], which is publicly available, as indicated by the “laptop”
icon. b The description of rs34500389 within database dbSNP [39]. c The results from our Web service SNP_TATA_Z-tester [31] for SNP
rs34500389 being analyzed. Dash-and-dot arrows: significance estimates for the alteration of the HBB level in patients with the minor allele (textbox “2nd promoter”) relative to the norm (text box “1st promoter”) expressed as a Z-score using the R package [43]. Circles indicate the ancestraland minor alleles of the SNP marker in question within the text boxes “1st promoter” and “2nd promoter,” respectively

the central nervous system (brain) of embryos, fetuses,
and adults [65]. The EPO–EPOR complex has an influence on the recovery and nutrition of brain tissues after
injury [66].
The GYPC gene codes for two sialoglycoproteins on
the erythrocyte surface in humans: glycophorin C (GPC)
and glycophorin D (GPD) [67]. Parasite P. falciparum,
which is a causative agent of malaria in humans, employs GPC to enter human erythrocytes. GYPC is widely
expressed in the large intestine, esophagus, and 23 otherorgans or tissues. Studies on the molecular evolution of
GYPC among hominids (great and smaller apes) and onpolymorphism patterns at the respective locus [67] haverevealed an excess of nonsynonymous between-species
divergences, which apparently are related to accelerated
evolution of GYPC in the Homo sapiens lineage.
DNA methylation is a hereditary epigenetic modification that stably changes the expression of genes involvedin such a complex mental disorder as schizophrenia.
Some researchers [68] have demonstrated that thePonomarenko et al. BMC Medical Genetics 2020, 21(Suppl 1):165

methylation profiles of GYPC, which contributes toschizophrenia pathogenesis, significantly differ between
female and male patients and between patients withschizophrenia and controls. Unannotated rs970970552,
identified by us as a candidate SNP marker via a prediction made by means of SNP_TATA_Z-tester, increases
the affinity between TBP and the TATA box of such asequence.
Experimental in vitro validation of the predictions about
the influence of SNPs on TBP–TATA affinity

For experimental in vitro validation, we chose SNPcontaining TATA boxes of human genes HBB, HBZ, andEPOR. Table 3 presents the results of in vitro verificationof our predictions regarding the influence of substitutions
in TATA boxes on TBP–TATA affinity. For instance,
TBP–TATA affinity in the HbZ promoter decreases 6.6fold as a result of a substitution in the TATA box(rs113180943), SNPs in the TATA-like sequence of thepromoter of EPOR (− 27 T > A, −31C > A, and -31C > G)enhancing the TBP–TATA affinity 15.5-fold, 8.1-fold, and2.1-fold, respectively. Additionally, Table 3 shows negative
natural logarithms of the predicted and experimentally determined KD values and changes in KD (δ) in the presenceof the SNP in the TATA box: δ = −ln [KD,Mut] – (−ln [KD,
WT]), and values of association and dissociation rate
constants (ka and kd, respectively) for TBP–TATA complexes, reflecting the velocities of their formation andPage 8 of 14

dissociation. The results were obtained in an electrophoretic mobility shift assay (Fig. 2): dependences of reaction
rates on deoxyoligonucleotide (hereinafter: ODN) concentrations – Fig. 2a; electropherograms, from which kinetic
curves were derived – Fig. 2b, − as well as one can see
Additional file 1: Supplementary Electropherogram.
Experimental validation of the influence of the unannotated SNP (rs34500389 located in НВВ) changing the
TATA box to a more canonical form (C-32ATAAAAAG → T-32ATAAAAAG) indicated, as predicted, an increase in TBP–TATA affinity (Table 3). This affinity forthe minor allele was 1.56-fold stronger (Table 3; KD =50 nM for the ancestral allele and 32 nM for the minor
allele) because of the greater (also 1.5-fold) velocity offormation of the complex. The dissociation velocity andlifetime of the complex barely changed. Perhaps the relatively small increase in affinity is explained by the presence of CATAAA in both flanks, i.e., a string of “АТ”
base pairs, which weaken the TBP–TATA binding.
The unannotated SNP (rs113180943, detected by us in
the TATA box of the HbZ promoter), which replaces
the third Т base (having the highest weight among thenucleotides in the TATA box sequence [69]) with “А,”according to the prediction, should weaken TBP–TATA
affinity. Experimental in vitro validation suggested that
this substitution indeed attenuates TBP–TATA affinity
6.6-fold (KD = 6 nM for the ancestral allele and KD = 40
nM for -29Т > А). The reason is that the velocity of

Table 3 Kinetic and thermodynamic characteristics of TBP–TATA interactions
Gene ODN Alleles:
WT or mut

AlleleSequences (5′ – 3′ strands),
26 bp

Prediction

Experiments-lnKD δ-lnKD δKD,
nM

16.81 +
17.26 0.45

50 ± 7 (1.4 ±32 ± 3 0.1)*104
2.1 ±0.1*104

agggctgggcataaaagtcagggcag 19.20 +agggctgggTataaaagtcagggcag 20.18 0.98

HbB

1
2

WT
rs34500389:T-32c > T

HbZ

3
4

WT
rs113180943:
A-29 t > A agctccctgtatataaggggaccctg 20.76 −1.48 18.93 −1.90 6 ± 1
agctccctgtaAataaggggaccctg 19.28
17.03
40 ±
20

EPOR 5WT

cacgtcatctatttttgtctgctacg 18.24

ka, M− 1s− 1

kd, s− 1

t1/2,
min

(7.1 ±
0.7)*10−4(6.6 ± 0,5)*10− 4

16 ± 217 ± 2(4.5 ± 0.4)
*104
(2.3 ± 0,2)*1033.0 ±0.6)*10−4(1.0 ±
0.4)*10− 4

38 ± 4
115 ±
15

15.59

170 ±
30

(2.8 ± 0,3)*103(4.6 ±
0.6)*10−4

25 ± 318.33 +
2.74

11 ± 3 (9.3 ± 0,7)*103(1.0 ±
0.3)*10−4

115 ±
15

6

rs1006576690: -27 t > A cacgtcatctatAtttgtctgctacg 19.39 +
A
1.15

7

rs971717705:
G-29a > G cacgtcatctGtttttgtctgctacg 18.11 −0.13 15.71 +
0.12

150 ±
30

(2.4 ± 0,3)*103(3.6 ±
0.5)*10−4

32 ± 48

rs567946217:
A-31c > A cacgtacatAttttttgtctgctacg 19.33 +1.09

17.68 +
2.09

21 ± 6 (6.8 ±0.7)*103(1.4 ±
0.4)*10−4

82 ± 69

rs567946217:
G-31c > G cacgtсatGtatttttgtctgctacg 18.51 +0.27

16.34 +
0.75

80 ±
10

(3.0 ±
0.5)*10−4

38 ± 4(3.6 ±
0.3)*103ODN Oligodeoxyribonucleotide; WT Ancestral allele; mut Minor allele; KD Equilibrium dissociation constant, which is presented as mean ± standard deviation; δ,the difference between the affinity of TBP for an ODN with and without the SNP in its TATA box expressed as natural logarithms, δ = −ln (KD,Mut) – [−ln (KD,WT)]; ka
and kd, association and dissociation rate constants, respectively; t1/2 = ln2/kd, the average half-life of the TBP/ODN complexes; HBB β-globin gene; HBZ Zeta-globin
gene; and EPOR Erythropoietin receptor genePonomarenko et al. BMC Medical Genetics 2020, 21(Suppl 1):165

Page 9 of 14

Fig. 2 Measuring the kinetics of TBP binding to TATA-containing ODN N2 identical to the HBB promoter in healthy people. Legend: a
Dependences of reaction rates on ODN N2 concentrations; b electropherograms from which these curves were derived. TBP concentration was
0.4 nM in all the experiments; the concentrations of a TATA-containing ODN that we used are indicated. TBP–TATA-associated isotherms and ka
and kd values were inferred from the electropherograms using GraphPad Prism 5 software

complex formation was 19.5-fold lower, dissociation velocity 3-fold lower, whereas the lifetime of the complex
was 3-fold longer.
The promoter of the erythropoietin receptor gene
(EPOR) contains a TATA-like sequence, ТАТТТТТG,
with the weightiest “Т” at the third position [69] butwith the flanks containing АТ pairs. This arrangement
results in weak TBP–TATA affinity: KD = 170 ± 30 nM.
The -27Т > А substitution strengthens this affinity 15.5fold. Of note, this enhancement of affinity is accompanied by only 3.3-fold greater velocity of formation of thecomplex and a 4.6-fold decrease in the velocity of its dissociation. The lifetime of the complex was more than 4fold longer in comparison with the reference allele. Incase of rs567946217 (−31С > А), adjacent to a TATA-

like sequence upstream, affinity was 8.1-fold stronger,
while the velocity of complex formation was 2.4-foldgreater, the velocity of dissociation 3.3-fold lower, andcomplex lifetime was > 3-fold greater. The -29А > G substitution (rs971717705), barely affecting TBP–TATA
affinity (KD strengthened by 13%), caused insignificant
changes in the velocities of formation and dissociation of
the complex (Table 3) and most likely can be categorized as a polymorphism causing “noise.” Rs567946217(−31С > G), replacing С (adjacent to the TATA box)with G, enhanced the affinity of the TBP–TATA bindingby 2-fold, raising the velocity of formation 1.3-fold anddecreasing the dissociation velocity 1.5-fold. The complex’s half-life also increased relative to the reference allele and was 38 min.

Ponomarenko et al. BMC Medical Genetics 2020, 21(Suppl 1):165

Significant correlations between our predictions in silico
and measurements in vitro

As presented in Fig. 3, our predicted and experimental
values significantly correlate with each other. As depictedin the graphs in the figure, for predicted KD and its experimental values expressed in ln units (−ln [KD]: Fig. 3a, andpredictions of measurements -ln [KD], δ: Fig. 3b) when the
SNP was present in TATA boxes, whose values are given
in Table 3, the coefficient of linear correlation r was 0.87
at p < 0.0025 and r = 0.91 (p < 0.001), respectively, whereas
δ was -ln [KD,Mut] – (−ln [KD,WT]). Finally, as readers cansee in Fig. 3, two considered reliable linear correlations between our predictions in silico and measurements in vitro
expressed in both absolute (a) and relative (b) scales weresuccessfully verified using three independent correlation
criteria, namely: the Goodman–Kruskal generalized correlation (γ), and both Spearman’s (R) and Kendall’s (τ)
rank correlations.
A comparison between the in vitro measurements of thiswork with those of other authors

It should be noted that the authors of some studies haveinvestigated the influence of a substitution of a first “Т”
with “С” in a TATA box sequence. For instance, in awork dealing with the TBP of the yeast Saccharomyces
cerevisiae [70], it was found that this substitution has
almost no influence on the binding. The same authors[71] have demonstrated that a promoter containing
sequence CATAAAA is 40-fold less effective at inducing
transcription in vivo than the classic sequence TATA
AAA. Other researchers [72] have shown that transcription in HeLa cells decreases 3-fold after a substitution ofPage 10 of 14

the first “Т” with “С” in the TATA box (TATA
AA→CATAAA). These examples reveal that the substitution of Т with С at the first position of the TATA box
has different effects on transcription and therefore on
the TBP–TATA interaction. One possible reason is differences in the sequences flanking the TATA box, because in some studies [73, 74], it has been reported thatthe affinity of TBP for oligonucleotides differing in thenumber of АТ pairs in the sequences flanking the TATAbox can differ 25- to 30-fold.
Our previously analyzed data on the relation of clinically confirmed diseases with substitutions in the TATA
boxes of the promoter of β-globin genes indicate thatthe phenotype of intermediate thalassemia is associatedwith changes in TBP–TATA affinity causing an imbalance of chains, on average by 2.0- to 2.6-fold [26]. Consequently, carriers of the rs34500389 allele featuring 1.5fold stronger TBP–TATA affinity may be susceptible tomild thalassemia because of the elevated amount of synthesized β-chains and can lead a normal lifestyle.
It is noteworthy that zeta-globin synthesis starts in theyolk sac in the third week of embryogenesis. By the fifth
week, its level drops, and fetal ɛ-globin synthesis is initiated. Downregulation of HbZ after the substitution in
the TATA box (rs113180943) can cause a stagedependent disruption of “switching” events for genes ofhemoglobins and the development of erythroblastosis[75]. In our study, experimental in vitro verification revealed that substitution -29Т > A (rs113180943) indeed
weakens TBP–TATA affinity 6.6-fold, and accordingly,
downregulates the gene. Thus, rs113180943 may be a
candidate SNP marker of severe hemoglobinopathies

Fig. 3 The significant correlations between the in silico predicted and in vitro experimentally measured values. Legend: a TBP–DNA affinity and b the TBP–DNA
affinity change caused by the minor allele of the analyzed SNPs with respect to the norm, −ln [KD] and Δln [KD], respectively. Solid and dashed lines denote thelinear regression and boundaries of its 95% confidence interval, calculated by means of software package STATISTICA (Statsoft™, USA); arrows pinpoint theancestral rs34500389:C and minor rs34500389:t alleles of the SNP being studied, an analysis of which is depicted in Fig. 1 as an example of the application of
our Web service SNP_TATA_Z-tester [31] in this work; r, τ, γ, and p are coefficients of Pearson’s linear correlation, Spearman’s rank correlation, Kendall’s rankcorrelation, and Goodman–Kruskal generalized correlation and their p values, respectively

Ponomarenko et al. BMC Medical Genetics 2020, 21(Suppl 1):165

comorbid with cognitive and mental disorders associatedwith disturbances of cerebral blood flow [14, 76–80]. It
should be noted that the experiment coincides well withthe prognosis, which is due to the TATA box sequenceclose to consensus. And this is especially true for “T” in
the third position of TATA box, which has the maximum weight among the nucleotides of the TATA box.
As a result of studying molecular and cellular programs regulating zeta-globin synthesis, some authors[81–83] have demonstrated its good potential as a new
therapeutic agent for α-thalassemia and sickle cellanemia. They found that after therapeutic reactivation, asilent but structurally intact gene of embryonic zetaglobin starts expression, and zeta-globin chains areassembled with adult β-globin into a heterotetramericcomplex, Hb z2β2, fully physiologically consistent withnormal adult hemoglobin [84]. This approach to αthalassemia treatment has been illustrated on a pathological phenotype of mice with homozygous embryonically lethal deactivation of α-globin genes [82];transgenic human zeta-globin makes these mice fully viable. Carriers of the minor allele of rs113180943 may
have hemoglobinopathy in addition to the higher risk ofmental disorders (more often bipolar disorder) associated with hypoxia or hyperoxia of the central nervous
system [8, 14].
There is evidence that glycoprotein hormone EPO is
the main regulator of erythrocyte formation and has
protective properties during cerebral ischemia [85]. To
perform its function, EPO binds to its receptor, EPOR,
which then dimerizes and activates, thereby inducing acascade of genes responsible for the proliferation, survival, and differentiation of erythroid progenitor cells[86]. Although in the blood, EPOR regulates erythrocyte
differentiation, in the brain, it protects several types ofneurons from death, including A9 dopaminergic neuronsof the substantia nigra [87], and promotes oxygen storage under hypoxia; this property of EPOR is especially
important for neurons with heightened needs for energy[11]. Several studies suggest that brain ischemia upregulates EPO and EPOR for repair of the damage [88, 89].
Accordingly, it can be hypothesized that SNPs in the
TATA-like sequence of the promoter of EPOR (− 27 T >A, −31C > A, and -31C > G) enhancing the TBP–TATA
affinity 15.5-fold, 8.1-fold, and 2.1-fold, respectively, inagreement with the expression levels of the gene, may
indicate some degree of hereditary ischemic damage tothe brain in the carriers of these alleles and may be candidate markers of this disorder. Substitutions -27 T > A
and -31C > A most likely may serve as SNP markers of arare disease, i.e., an erythropoiesis disorder [14] causedby an excessive number of erythrocytes.
The results of some experiments [77, 78] point to theparticipation of hemoglobins in mitochondrial respiration

Page 11 of 14

and metabolism. Therefore, both hypoxia and hyperoxia can damage brain tissues either by blocking ATP
production or by increasing the formation of reactive
oxygen species. Consequently, hemoglobins involved
in mitochondrial metabolism and oxidative phosphorylation can have a major influence on neuron integrity and neurodegenerative events, which play a rolein the pathogenesis of cognitive and mental disorders[14, 90]. On the other hand, SNPs -27 T > A and-31C > A, which cause a greater enhancement of
TBP–TATA affinity and therefore upregulation of
EPOR, may be candidate markers of increased risk ofcognitive and mental disorders. This notion is supported by many studies indicating that both lowerand higher levels of hemoglobin are related to an accelerated cognitive impairment [12, 13, 87–92].

Conclusion
It is known that genes of hemoglobins are expressed in
the astrocytes of the cortex and hippocampus and inoligodendroglia that is located in almost all brain regions,
including the striatum, corpus collosum, and medulla[11]. There are many reports about the correlation between aberrations in the metabolism of hemoglobins andsymptoms of mental disorders [12, 88–93]. Many investigators believe that cognitive deficits are a cause not a consequence of erythropoiesis disturbances [12, 91–97].
Thus, from previous literature data as well as our computational and experimental results, it can be concluded
that the identified candidate SNP markers of erythropoiesis disturbances may also be studied in cohorts of patients with cognitive and/or mental disorders withcomorbid erythropoiesis diseases in comparison to conventionally healthy volunteers. Research on the regulatory mechanisms—by which the uncovered SNP markers
contribute to the development of hemoglobinopathies
and the comorbid cognitive deficits—will help physicians
to not only take timely and adequate measures against
hemoglobinopathies but also to implement strategies
preventing or slowing the progression of cognitive andmental disorders. This new knowledge is an additional
resource for biomedical research, personalized medicine,diagnostics, and the development of therapeutics.
Finally, because we have already verified our in silico
predictions in question using ex vivo transfections of thepGL4.10 plasmid with LUC gene-reporter (Promega,
USA) into both cancer cell cultures (e.g., HCT116) [35]and fibroblast ones (e.g., hTERT-BJ1) [98], a recent cellreprogramming technologies based on the induced
pluripotent stem cell lines aimed to simulate neurodegenerations (e.g., ICGi007-A [99]) would in future give achance for more-or-less adequate testing ex vivo thecandidate SNP markers of neuropathogenesis as soon as
it could be free-available and well-studied.

Ponomarenko et al. BMC Medical Genetics 2020, 21(Suppl 1):165

Supplementary information
Supplementary information accompanies this paper at https://doi.org/10.
1186/s12881-020-01106-x.
Additional file 1: Supplementary Electropherogram. The original,
raw, unfiltered, uncropped, unedited electropherogram used for Fig. 2b
in the cases of the minor allele T of the unannotated SNP rs34500389 of
the human HBB gene promoter under this study.
Abbreviations
EMSA: Electrophoretic mobility shift assay; ka and kd: Association anddissociation rate constants, respectively; KD = kd / ka: Equilibrium dissociation
constant; ln: Natural logarithm; mut: Minor allele;
ODN: Oligodeoxyribonucleotide; SNP: Single-nucleotide polymorphism;
TBP: TATA-binding protein; TBP-site: TBP-binding site; t1/2 = ln2/kd: Theaverage half-life of the TBP/ODN complexes; WT: Wild type (norm); δ: The
difference between the affinity of TBP for an ODN with and without the SNP
in its TATA box expressed as natural logarithms; ALAS1: Aminolevulinate
synthase 1; CA1: Carbonic anhydrase 1; CA1_2: Carbonic anhydrase promoter
2; EDRF1: Erythroid differentiation regulatory factor 1; EPOR: Erythropoietin
receptor; GYPB: Glycophorin B; GYPC: Glycophorin C; HBA1: α1-globin; HBB: βglobin; HBB_2: β-globin promoter 2; HBG1: Aγ globin; HBE1: ε-globin;
HBM: Hemoglobin μ; HBZ: Zeta-globin; HBZ_3: Zeta-globin promoter 3;
HOXB2: Homeobox B2
Acknowledgments
We are grateful to Shevchuk Editing (Brooklyn, NY, USA;http://www.
shevchuk-editing.com) for English translation and editing.
About this supplement
This article has been published as part of BMC Medical Genetics Volume 21
Supplement 1, 2020: Selected Topics in “Systems Biology and Bioinformatics”- 2019: medical genetics. The full contents of the supplement are available
online at https://bmcmedgenet.biomedcentral.com/articles/supplements/
volume-21-supplement-1.
Authors’ contributions
NK and LS conceived of and supervised the study. ID, ES, and IC conducted
the in vitro experiments. PP, OP, and MP designed, developed, maintained,
adapted, and tuned the software for sequence analysis. OA analyzed thedata in silico. MP and LS interpreted the computer-based predictions in comparison with experimental data. LS wrote the manuscript. All the coauthors
read and approved the final version of the manuscript.
Funding
Manuscript writing was supported by project #0324–2019-0042-C-01 fromthe Russian Government Budget (for LS, OA and ID). The data compilation
was supported by project #0324–2019-0040-C-01 from the Russian
Government Budget (for IC, PP, and OP). The in vitro experiment was
supported by the project “Investigation, analysis and complex independent
expertise of projects of the National technological initiatives, including theaccompanying projects of the road map “NeuroNet,” which is executed
within the framework of state assignment #28.12487.2018/12.1 (for ES) and“5–100″ (for MP) from the Ministry of Science and Higher Education of theRussian Federation.
Publication costs have been funded by the Russian Federal Science &Technology Program for the Development of Genetic Technologies.
All the authors declare that these funding bodies did not play roles in thedesign of the study and collection, analysis, and interpretation of data and inwriting the manuscript.
Availability of data and materials
Web service SNP_TATA_Z-tester is publicly available (http://wwwmgs.bionet.
nsc.ru/cgi-bin/mgs/tatascan_fox/start.pl).
Due to two publicly available Web services UCSC Genome Browser (URL =http://genome.ucsc.edu/) [38] and NCBI dbSNP database build No.151 (URL
= http://www.ncbi.nlm.nih.gov/snp/) [39], we predicted SNPs, which canreliably cause over- and underexpression of the 13 human erythroid genes
HBB, HBZ, HBA1, HBG1, HBM, HBE1, ALAS1, CA1, HOXB2, EPOR, GYPB, GYPC,EDRF1 and IDs of which are listed, as follows: rs1006576690, rs1035033590,

Page 12 of 14

rs1036491581, rs1046254329, rs113180943, rs150246840, rs281864525,
rs33931746, rs33980857, rs33981098, rs34500389, rs34598529, rs35518301,
rs3967038, rs538698304, rs540950375, rs557418569, rs559282746,
rs564394089, rs567946217, rs571582665, rs573241527, rs63750400,
rs762972656, rs768296486, rs774081749, rs895690311, rs905035347,
rs905730148, rs911469201, rs937192507, rs946240545, rs970970552,
rs971717705, rs989175270, and rs991064314.
Ethics approval and consent to participate
Not applicable.
Consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Author details
1
Institute of Cytology and Genetics, Siberian Branch of Russian Academy of
Sciences, 10 Lavrentyev Ave, Novosibirsk 630090, Russia. 2Novosibirsk State
University, 1 Pirogova Street, Novosibirsk 630090, Russia. 3Institute of Gene
Biology Russian Academy of Sciences, 34/5 Vavilova Street, Moscow 119334,
Russia.
Published: 22 October 2020
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